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    Publications

    • Schulte L; Butz M; Becker M; Risse B; Schuck C. . ‘Accelerating Finite-Difference Frequency-Domain Simulations for Inverse Design Problems in Nanophotonics using Deep Learning .’ Journal of the Optical Society of America B 41, No. 4: 1039–1046. doi: 10.1364/JOSAB.506159.
    • Kockwelp, Jacqueline; Thiele, Sebastian; Bartsch, Jannis; Haalck, Lars; Gromoll, Jörg; Schlatt, Stefan; Exeler, Rita; Bleckmann, Annalen; Lenz, Georg; Wolf, Sebastian; Steffen, Björn; Berdel, Wolfgang Eduard; Schliemann, Christoph; Risse, Benjamin; Angenendt, Linus. . ‘Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears.’ Blood Advances 8, No. 1: 70–79. doi: 10.1182/bloodadvances.2023011076.
    • Beckmann, Daniel; Kockwelp, Jacqueline; Gromoll, Joerg; Kiefer, Friedemann;Risse, Benjamin. . ‘SAM meets Gaze: Passive Eye Tracking for Prompt-based Instance Segmentation.’ Proceedings of Machine Learning Research . [accepted / in Press (not yet published)]
    • Haalck, Lars; Risse, Benjamin. . ‘Solving the Plane-Sphere Ambiguity in Top-Down Structure-from-Motion.’ Contributed to the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii. [accepted / in Press (not yet published)]
    • Gebauer, Eike; Thiele, Sebastian; Ouvrard, Pierre; Sicard, Adrien; Risse, Benjamin. . ‘Towards a Dynamic Vision Sensor-based Insect Camera Trap.’ Contributed to the Winter Conference on Applications of Computer Vision 2024, Waikoloa, Hawaii. [accepted / in Press (not yet published)]
    • Young S; Schiffer C; Wagner A; Patz J; Potapenko A; Herrmann L; Nordhoff V; Pock T; Krallmann C; Stallmeyer B; Röpke A; Kierzek M; Biagioni C; Wang T; Haalck L; Deuster D; Hansen JN; Wachten D; Risse B; Behre HM; Schlatt S; Kliesch S; Tüttelmann F; Brenker C; Strünker T. . ‘Human fertilization in vivo and in vitro requires the CatSper channel to initiate sperm hyperactivation.’ Journal of Clinical Investigation 134, No. 1. doi: 10.1172/JCI173564.
    • Winter NR; Blanke J; Leenings R; Ernsting J; Fisch L; Sarink K; Barkhau C; Emden D; Thiel K; Flinkenflügel K; Winter A; Goltermann J; Meinert S; Dohm K; Repple J; Gruber M; Leehr EJ; Opel N; Grotegerd D; Redlich R; Nitsch R; Bauer J; Heindel W; Gross J; Risse B; Andlauer TFM; Forstner AJ; Nöthen MM; Rietschel M; Hofmann SG; Pfarr JK; Teutenberg L; Usemann P; Thomas-Odenthal F; Wroblewski A; Brosch K; Stein F; Jansen A; Jamalabadi H; Alexander N; Straube B; Nenadic I; Kircher T; Dannlowski U; Hahn T. . ‘A Systematic Evaluation of Machine Learning--Based Biomarkers for Major Depressive Disorder.’ JAMA Psychiatry . doi: 10.1001/jamapsychiatry.2023.5083. [accepted / in Press (not yet published)]
    • Bauer N; Beckmann D; Reinhardt D; Frost N; Bobe S; Erapaneedi R; Risse B; Kiefer F. . ‘Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction.’ Scientific Reports 14, No. 1: 2034. doi: https://doi.org/10.1038/s41598-024-52268-0.

    • Barrie, Robert; Haalck, Lars; Risse, Benjamin; Nowotny, Thomas; Graham, Paul; Buehlman, Cornelia. . ‘Trail using ants follow idiosyncratic routes in complex landscapes.’ Learning and Behavior s13420-023-00615. doi: https://doi.org/10.3758/s13420-023-00615-y.
    • Hätscher Ole , Junga Anna , Schulze Henriette , Kockwelp Pascal , Risse Benjamin , Back D. Mitja , Marschall Bernhard.Zusammenhang von Persönlichkeitsvariablen und Leistung in der virtuellen medizinischen Ausbildung.’ contributed to the Jahrestagung der Gesellschaft für medizinische Ausbildung (GMA) 2023, Osnabrück, . doi: 10.3205/23GMA273.
    • Mergen, M; Junga, Anna, Risse, Benjamin; Valkov, Dimitar; Graf, Norbert; Marschall, Bernhard; Medical Tr.AI.Ning Consortium. . „Immersive training of clinical decision making with AI driven virtual patients – a new VR platform called medical tr.AI.ning.“ GMS Journal for Medical Education 40, No. 2. doi: 10.3205/ZMA001600.
    • Butz, Marco; Abazi, Adrian S.; Ross, Rene; Risse, Benjamin; Schuck, Carsten. . ‘Inverse Design of Nanophotonic Devices using Dynamic Binarization.’ Optics Express 31, No. 10: 15747–15756. doi: 10.1364/OE.484484.
    • Wendland D; Becker M; Brückerhoff-Plückelmann F; Bente I; Busch K; Risse B; Pernice WH. . ‘Coherent dimension reduction with integrated photonic circuits exploiting tailored disorder.’ Journal of the Optical Society of America B 40, No. 3: B35–B40.
    • Haalck L; Mangan M; Wystrach A; Clement L; Webb B; Risse B. . ‘CATER: Combined Animal Tracking & Environment Reconstruction.’ Science advances 9, No. 16: eadg2094.
    • Rösler W; Altenbuchinger M; Bae{ß}ler B; Beissbarth T; Beutel G; Bock R; Bubnoff N; Eckardt J; Foersch S; Loeffler CM; others. . ‘An overview and a roadmap for artificial intelligence in hematology and oncology.’ Journal of Cancer Research and Clinical Oncology 15: 1–10.
    • Butz M; Leifhelm A; Becker M; Risse B; Schuck C. . ‘A Universal Approach to Nanophotonic Inverse Design through Reinforcement Learning.’ In CLEO 2023, paper STh4G.3, edited by Optica Publishing Group, STh4G.3. San Jose: Optica. doi: 10.1364/CLEO_SI.2023.STh4G.3.
    • Butz, Marco; Leifhelm, Alexander; Becker, Marlon; Risse, Benjamin; Schuck, Carsten. . ‘A Novel Approach to Nanophotonic Black-Box Optimization Through Reinforcement Learning.’ In Q 30 Nano-optics, edited by DPG, 1. Hannover: Deutsche Physikalische Gesellschaft.
    • Kockwelp, Jacqueline; Gromoll, Jörg; Wistuba, Joachim; Risse, Benjamin. . ‘EyeGuide - From Gaze Data to Instance Segmentation.’ Contributed to the The British Machine Vision Conference (BMVC), Aberdeen.
    • Becker, Marlon; Riegelmeyer, Jan; Seyfried, Maximilian; Ravoo, Bart-Jan; Schuck, Carsten; Risse, Benjamin. . ‘Adaptive Photo-Chemical Nonlinearities for Optical Neural Networks.’ Advanced Intelligent Systems ‎ 5, No. 12: 2300229. doi: 10.1002/aisy.202300229 .
    • Haalck, Lars; Thiele, Sebastian; Risse, Benjamin. . ‘Tracking Tiny Insects in Cluttered Natural Environments using Refinable Recurrent Neural Networks.’ Contributed to the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii. [accepted / in Press (not yet published)]
    • Brückerhoff-Plückelmann, Frank; Bente, Ivonne; Becker, Marlon; Vollmar, Niklas; Farmakidis, Nikolaos; Lomonte, Emma; Lenzini, Francesco; Wright, C David; Bhaskaran, Harish; Salinga, Martin; Risse, Benjamin; Pernice, Wolfram HP. . ‘Event-driven adaptive optical neural network.’ Science advances 9, No. 42: eadi9127. doi: 10.1126/sciadv.adi9127.
    • Becker, Marlon; Drees, Dominik; Brückerhoff-Plückelmann, Frank; Schuck, Carsten; Pernice, Wolfram; Risse, Benjamin.Activation Functions in Non-Negative Neural Networks.’ contributed to the Machine Learning and the Physical Sciences Workshop, NeurIPS, New Orleans, .
    • Pielage, Leon; Schmidle, Paul; Marschall, Bernhard; Risse, Benjamin.Diffusion Models in Dermatological Education: Flexible High Quality Image Generation for VR-based Clinical Simulations.’ contributed to the NeurIPS'23 Workshop: Generative AI for Education (GAIED), New Orleans, Louisiana, .
    • Döll, Petra; Sester, Monika; Feuerhake, Udo; Frahm, Holger; Fritzsch, Bernadette; Hezel, Dominik C; Kaus, Boris; Kolditz, Olaf; Linxweiler, Jan; Müller Schmied, Hannes; Nyenah, Emmanuel; Risse, Benjamin; Schielein, Ulrich; Schlauch, Tobias; Streck, Thilo; van den Oord, Gijs. . Sustainable research software for high-quality computational research in the Earth System Sciences: Recommendations for universities, funders and the scientific community in Germany FIG GEO-LEO e-docs. doi: 10.23689/fidgeo-5805.
    • Becker, Marlon; Riegelmeyer, Jan; Seyfried, Maximilian David; Ravoo, Bart Jan; Schuck, Carsten; Risse, Benjamin. . ‘Adaptive Photochemical Nonlinearities for Optical Neural Networks.’ Advanced Intelligent Systems 5, No. 12. doi: 10.1002/aisy.202300229.
    • Becker, Marlon; Butz, Marco; Lemli, David; Schuck, Carsten; Risse, Benjamin.Combinatorial Optimization via Memory Metropolis: Template Networks for Proposal Distributions in Simulated Annealing applied to Nanophotonic Inverse Design.’ contributed to the Neural Information Processing Systems (NeurIPS) Workshop on AI for Accelerated Materials Design (AI4Mat-2023), New Orleans, .
    • Mergen, Marvin*; Junga, Anna*; Risse, Benjamin; Valkov, Dimitar; Graf, Norbert; Marschall, Bernhard. . ‘Immersive training of clinical decision making with AI driven virtual patients-a new VR platform called medical tr.AI.ning.’ GMS Journal for Medical Education 40, No. 2. doi: 10.3205/zma001600.

    • Junga, Anna; Kockwelp, Pascal; Valkov, Dimitar; Marschall, Bernhard; Hartwig, Sophia; Stummer, Walter; Risse, Benjamin; Holling, Markus.Virtual Reality based teaching – a paradigm shift in education?’ contributed to the 73. Jahrestagung Deutsche Gesellschaft für Neurochirurgie, Köln, . doi: 10.3205/22DGNC538.
    • Bobe S, Beckmann D, Klump DM, Dierkes C, Kirschnick N, Redder E, Bauer N, Schäfers M, Erapaneedi R, Risse B, van de Pavert SA, Kiefer F. . ‘Volumetric imaging reveals VEGF-C-dependent formation of hepatic lymph vessels in mice.Frontiers in cell and developmental biology 10: 949896. doi: 10.3389/fcell.2022.949896.
    • Hahn T, Ernsting J, Winter NR, Holstein V, Leenings R, Beisemann M, Fisch L, Sarink K, Emden D, Opel N, Redlich R, Repple J, Grotegerd D, Meinert S, Hirsch JG, Niendorf T, Endemann B, Bamberg F, Kröncke T, Bülow R, Völzke H, von Stackelberg O, Sowade RF, Umutlu L, Schmidt B, Caspers S, Kugel H, Kircher T, Risse B, Gaser C, Cole JH, Dannlowski U, Berger K. . ‘An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling.’ Science advances 8, No. 1: eabg9471. doi: 10.1126/sciadv.abg9471.
    • Tuia D, Kellenberger B, Beery S, Costelloe BR, Zuffi S, Risse B, Mathis A, Mathis MW, van Langevelde F, Burghardt T, Kays R, Klinck H, Wikelski M, Couzin ID, van Horn G, Crofoot MC, Stewart CV, Berger-Wolf T. . ‘Perspectives in machine learning for wildlife conservation.’ Nature Communications 13, No. 1: 792–807. doi: 10.1038/s41467-022-27980-y.
    • Kockwelp P, Junga A, Valkov D, Marschall B, Holling M, Risse B. . ‘Towards VR Simulation-Based Training in Brain Death Determination.’ In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), edited by IEEE, 287–292. 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW): Wiley-IEEE Press.
    • Thiele, Sebastian; Risse, Benjamin. . ‘Narrowing Attention in Capsule Networks.’ In 26th International Conference on Pattern Recognition, edited by IEEE, 2679–2685. 26th International Conference on Pattern Recognition (ICPR): Wiley-IEEE Press.
    • Kockwelp, Jacqueline; Thiele, Sebastian; Kockwelp, Pascal; Bartsch, Jannis; Schliemann, Christoph; Angenendt, Linus; Risse, Benjamin. . ‘Cell Selection-based Data Reduction Pipeline for Whole Slide Image Analysis of Acute Myeloid Leukemia.’ In The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), edited by IEEE/CVF, 1825–1834. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition: Wiley-IEEE Press.
    • Riegelmeyer, Jan; Eich, Alexander;Becker, Marlon;Risse, Benjamin;Schuck, Carsten.Development of a nanophotonic nonlinear unit for optical artificial neural networks.’ contributed to the DPG Springmeeting 2022, Erlangen, .
    • Butz, Marco; Leifhelm, Alexander; Becker, Marlon; Risse, Benjamin; Schuck, Carsten. . ‘Inverse Design of Nanophotonic Devices based on Reinforcement Learning.’ In Q 38 Photonics II, edited by DPG, 2. Erlangen: Deutsche Physikalische Gesellschaft.

    • Bian A, Jiang X, Berh D, Risse B. . ‘Resolving colliding larvae by fitting ASM to random walker-based pre-segmentations.’ IEEE/ACM Transactions on Computational Biology and Bioinformatics 18, No. 3: 1184–1194.
    • Valkov Dimitar, Thiele Sebastian, Huesmann Karim, Risse Benjamin. . ‘Touch Recognition on Complex 3D Printed Surfaces using Filter Response Analysis.’ Contributed to the IEEE VR Workshop on Novel Input Devices and Interaction Techniques (NIDIT), Online. [online first]
    • Huesmann Karim, Rodriguez Luis Garcia, Linsen Lars, Risse Benjamin. . ‘The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks.’ In The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks.: Springer International Publishing.
    • Haalck Lars, Risse Benjamin. . ‘Embedded Dense Camera Trajectories in Multi-Video Image Mosaics by Geodesic Interpolation-based Reintegration.’ Contributed to the Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii.
    • Thiele Sebastian, Haalck Lars, Struffert Marvin, Scherber Christoph, Risse Benjamin. . ‘Towards Visual Insect Camera Traps.’ Contributed to the International Conference on Pattern Recognition (ICPR) Workshop on Visual observation and analysis of Vertebrate And Insect Behavior (VAIB), Milan.
    • Leenings R, Winter NR, Plagwitz L, Holstein V, Ernsting J, Sarink K, Fisch L, Steenweg J, Kleine-Vennekate L, Gebker J, Emden D, Grotegerd D, Opel N, Risse B, Jiang X, Dannlowski U, Hahn T. . ‘PHOTONAI-A Python API for rapid machine learning model development .’ PloS one 16. doi: 10.1371/journal.pone.0254062.

    • Huesmann K, Klemm S, Linsen L, Risse B. . Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization. arXiv e-print:2002.09237: CoRR.
    • Leenings R, Winter NR, Plagwitz L, Holstein V, Ernsting J, Steenweg J, Gebker J, Sarink K, Emden D, Grotegerd D, others. . ‘PHOTON--A Python API for Rapid Machine Learning Model Development.’ arXiv preprint arXiv:2002.05426 2020.
    • Neuert H, Deing P, Krukkert K, Naffin E, Steffes G, Risse B, Silies M, Klämbt C. . ‘The Drosophila NCAM homolog Fas2 signals independently of adhesion.’ Development 147, No. 2. doi: 10.1242/dev.181479.
    • Haalck L, Mangan M, Webb B, Risse B. . ‘Towards image-based animal tracking in natural environments using a freely moving camera.’ Journal of Neuroscience Methods 330: 108455. doi: 10.1016/j.jneumeth.2019.108455.

    • Gkanias E, Risse B, Mangan M, Webb B. . ‘From skylight input to behavioural output: a computational model of the insect polarised light compass.’ PLoS Computational Biology 15, No. 7: e1007123. doi: 10.1371/journal.pcbi.1007123.

    • Berh D, Scherzinger A, Otto N, Jiang X, Klämbt C, Risse B. . ‘Automatic non-invasive heartbeat quantification of Drosophila pupae.’ Computers in Biology and Medicine 93: 189–199.
    • Otto N, Marelja Z, Schoofs A, Kranenburg H, Bittern J, Yildirim K, Berh D, Bethke M, Thomas S, Rode S, Risse B, Jiang X, Pankratz M, Leimkuehler S, Klämbt C. . ‘The Sulfite Oxidase Shopper controls neuronal activity by regulating glutamate homeostasis in Drosophila ensheathing glia.’ Nature Communications 9, No. 1: 3514.
    • Kiel M, Berh D, Daniel J, Otto N, Steege A, Jiang X, Liebau E, Risse B. . A Multi-Purpose Worm Tracker Based on FIM bioRxiv.
    • Risse B, Mangan M, Webb B.Possibilities, Constraints and Limitations of Image-based Animal Tracking in Natural Environments.’ contributed to the Measuring Behavior, Manchester, UK, . [online first]
    • Risse B, Mangan M, Stürzl W, Webb B. . ‘Software to convert terrestrial LiDAR scans of natural environments into photorealistic meshes.’ Environmental Modelling and Software 99: 88–100. doi: 10.1016/j.envsoft.2017.09.018.
    • Klemm S, Jiang X, Risse B. . ‘Deep distance transform to segment visually indistinguishable merged objects.’ Contributed to the Proc. of 40th German Conference on Pattern Recognition (GCPR), Stuttgart.

    • Almeida-Carvalho MJ, Berh D, ......, Jiang X, ......, Risse B, ......, Zlatic M. . ‘The Ol1mpiad: Concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae.’ Journal of Experimental Biology 220: 2452–2475. doi: 10.1242/jeb.156646.
    • Risse B, Berh D, Otto N, Klämbt C, Jiang X. . ‘FIMTrack: An open source tracking and locomotion analysis software for small animals.’ PLoS Computational Biology 13, No. 5: e1005530. doi: 10.1371/journal.pcbi.1005530.
    • Berh D, Risse B, Michels T, Otto N, Jiang X, Klämbt C. . ‘A FIM-based long-term in-vial monitoring system for Drosophila larvae.’ IEEE Transactions on Biomedical Engineering 64, No. 8: 1862–1874.
    • Risse B, Mangan M, Del Pero L, Webb B. . ‘Visual Tracking of Small Animals in Cluttered Natural Environments Using a Freely Moving Camera.’ International Conference on Computer Vision (ICCV), Workshop on Visual Wildlife Monitoring, Venice, Italy 2017: 2840–2849.

    • Otto N, Risse B, Berh D, Bittern J, Jiang X, Klämbt C. . ‘Interactions among Drosophila larvae before and during collision.’ Scientific Reports 11, No. 6: 31564. doi: 10.1038/srep31564.
    • Risse B, Mangan M, Webb B.Tracking, Mapping and Reconstruction. Modelling the Visual Perception of Desert Ants.’ contributed to the Animal Movement International Symposium, Lund, Sweden, .
    • Risse B, Mangan M, Webb B.Habitat3D: Recreating the History of Visual Experience of Individual Insects.’ contributed to the International Congress of Neuroethology, Montevideo, Uruguay, .
    • Risse B, Mangan M, Del Pero L, Webb B.HabiTracks: Visual Tracking of Insects in Their Natural Habitat.’ contributed to the International Congress of Neuroethology, Montevideo, Uruguay, .
    • Risse B, Otto N, Berh D, Jiang X, Kiel M, Klämbt C. . ‘FIM2c : A Multi-Colour, Multi-Purpose Imaging System to Manipulate and Analyse Animal Behaviour.IEEE Transactions on Biomedical Engineering 64: 1–1.

    • Risse B., Berh D., Otto N., Jiang X., Klämbt C. . ‘Quantifying subtle locomotion phenotypes of Drosophila larvae using internal structures based on FIM images.’ Computers in Biology and Medicine 63, No. null: 269–276. doi: 10.1016/j.compbiomed.2014.08.026.

    • Risse B, Berh D, Otto N, Jiang X, Klämbt C. . ‘Imaging Modalities for Semi-Translucent Animals and Their Impact on Quantitative Analysis.’ In VAIB Workshop, ICPR, 1–4.
    • B. Risse, N. Otto, D. Berh, X. Jiang, C. Klämbt. . ‘FIM imaging and FIMTrack: Two new tools allowing high-throughput and cost effective locomotion analysis.’ Journal of Visualized Experiments 94.
    • U. Lammel, M. Bechtold, B. Risse B, D. Berh, A. Fleige, I. Bunse, X. Jiang, C. Klämbt, S. Bogdan. . ‘The Drosophila FHOD1-like formin Knittrig acts through Rok to promote stress fiber formation and directed macrophage migration during the cellular immune response.Development 141, No. 6: 1366–1380. doi: 10.1242/dev.101352.
    • Tao J, Risse B, Jiang X. . ‘Stereo and Motion Based 3D High Density Object Tracking.’ Image and Video Technology 2014: 136–148. doi: 10.1007/978-3-642-53842-1_12.
    • Risse B, Berh D, Otto N, Jiang X, Klämbt C.FIM2C and the Analysis of Collision Behavior.’ contributed to the Flies, Worms and Robots: Combining Perspectives on Minibrains and Behavior Conference, Sant Feliu de Guixols, Spain, .

    • Jiang X, Dawood M, Gigengack F, Risse B, Schmid S, Tenbrinck D, Schäfers K. . ‘Biomedical Imaging: a Computer Vision Perspective.’ In Computer Analysis of Images and Patterns, edited by R. Wilson et al.: CAIP 2013, 1–19. Berlin, Heidelberg: Springer VDI Verlag.
    • Risse B, Jiang X, Klämbt C. . ‘FIM: Frustrated Total Internal Reflection Based Imaging for Biomedical Applications.’ ERCIM News 95, No. Image Understanding: 11–12.
    • M. Sander, A.J. Squarr, B. Risse, X. Jiang, S. Bogdan. . ‘Drosophila pupal macrophages - A versatile tool for combined ex vivo and in vivo imaging of actin dynamics at high resolution.European Journal of Cell Biology 2013. doi: 10.1016/j.ejcb.2013.09.003.
    • B. Risse, S. Thomas, N. Otto, T. Löpmeier, D. Valkov, X. Jiang, C. Klämbt. . ‘FIM, a novel FTIR-based imaging method for high throughput locomotion analysis.’ PloS one 8, No. 1: e53963. doi: 10.1371/journal.pone.0053963.
    • Risse B, Berh D, Tao J, Jiang X, Klette R, Klämbt C. . ‘Comparison of two 3D tracking paradigms for freely flying insects.’ EURASIP J Image Video Process 2013, No. 1: 57. doi: 10.1186/1687-5281-2013-57.
    • Risse B, Otto N, Berh D, Jiang X, Klämbt C.Tracking of Colliding Larvae.’ contributed to the Conference on Neurobiology of Drosophila, New York, USA, .

    • Schmidt I, Thomas S, Kain P, Risse B, Naffin E, Klämbt C. . ‘Kinesin heavy chain function in Drosophila glial cells controls neuronal activity.Journal of Neuroscience 32, No. 22: 7466–7476. doi: 10.1523/JNEUROSCI.0349-12.2012.
    • Tao J, Risse B, Jiang X, Klette R. . ‘3D Trajectory Estimation of Simulated Fruit Flies.’ In Proc 27th IVCNZ, Dunedin 2012.
    • Risse B, Thomas S, Jiang X, Klämbt C.FIM: FTIR Based Image Acquisition and Tracking.’ contributed to the Conference on Behavioral Neurogenetics of Drosophila Larva (Maggot Meeting), Ashburn, USA, .
  •  

    Talks

    • Ernsting, Jan (): ‘An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling’. Virtual St. Andrews-Bonn meeting: Early career focus - focused on techniques rather than results, Online, .

    • Risse, Benjamin (): „KI als anthropologische Herausforderung: Durchbrüche und Grenzen ak- tueller KI Entwicklungen“. Seminar in Humanities, University of Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘From the Lab to the Field - Novel Computer Vision and Machine Learning Approaches to Quantify the Behaviour of Animals Across Scales’. NC3 Symposium, University of Bielefeld, Bielefeld, Germany, .
    • Risse, Benjamin; Hiltmann, Thorsten (): „How deep learning based image analysis and cultural historical heraldry benefit from each other“. Konference: Digital Humanities Deutschland (DHD2020), University of Paderborn, Paderborn, Germany, .
    • Risse, Benjamin (): ‘The Benefits of Interdisciplinary Machine Learning & Computer Vision Research’. Center for Reproductive Medicine and Andrology, University Hospital Münster, Münster, Germany, .

    • Risse, Benjamin (): „Machine Learning & Computer Vision in Interdisciplinary Research“. eScience Symposium, University of Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Is Science Mostly Driven by Ideas or By Tools?’ Semiar: Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Interdisciplinary Research at the Interface of Behavioural Biology and Com- puter Vision & Machine Learning’. Invited Talk MPI Bonn, MPI Bonn, Bonn, Germany, .
    • Risse, Benjamin (): ‘"Artificial intelligence" - The quintessence of scientific narrow-mindedness?’ Lecture series on Digitisation, Privacy and AI, University of Münster, Münster, Germany, .
    • Haalck, Lars; Risse, Benjamin (): ‘Quantifying the Behavioural Dynamics Behind the Sixth Mass Extinction of Insects – A Progress Report’. EnviroInfo 2019, Kassel, Deutschland, .
    • Risse, Benjamin (): ‘Machine Learning: Yet Another Quantitative Research Tool’. CiM Symposium, University of Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Visual Tracking of Tiny Insects Using a Freely Moving Camera While Reconstructing Their Environment’. Conference: Association for the Study of Animal Behaviour (ASAB), University of Konstanz, Konstanz, Germany, .
    • Risse, Benjamin (): ‘Automatic Recognition of Wildlife Animals in Camera Trap Images’. Hoge Veluwe National Park Open Day, Hoge Veluwe National Park, Netherlands, .
    • Risse, Benjamin (): ‘Machine Learning for Image Analysis’. GI at School, University of Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Informatik Studieren?’ Berufsinformationstag BIBO 2019, Oelde, Germany, .
    • Risse, Benjamin (): ‘Detecting and Tracking Animals in Complex Natural Environments’. Invitation of the BBC Manchester, BBC Manchester, Manchester, UK, .
    • Risse, Benjamin (): ‘Tracking the Untrackable: Detecting Tiny Objects in Heavily Cluttered Environments’. Seminar in the University Hospital Münster , University Hospital Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Tracking Tiny Objects While Reconstructing Their Natural Environment Using Hand-held Cameras and Drones’. Seminar at the Institute of Landscape Ecology, WWU Münster, Münster, Deutschland, .

    • Risse, Benjamin (): ‘Machine Learning and Computer Vision - Tools & Technical Challenges’. BASF Scientific Meeting, Mannheim, Germany, .
    • Risse, Benjamin (): ‘Machine Learning & Computer Vision for In-Vial Tracking’. Young Academy Retreat of the Cells in Motion Cluster of Excellence, WWU Münster, .
    • Risse, Benjamin (): ‘Possibilities, Constraints and Limitations of Image-based Animal Tracking in Natural Environments’. Measuring Behavior Conference, Manchester, UK, .
    • Risse, Benjamin (): ‘From Hand-held Cameras to Drones: Tracking Tiny Objects while Recon- (est.) structing the Environment’. Geoinformatik Münster, Münster, Germany, .
    • Risse, Benjamin (): ‘Computer Vision in the Wild’. Laboratory of Geo-Information Science and Remote Sensing, Wageningen, Netherlands, .
    • Risse, Benjamin (): ‘Computer Vision in the Wild’. Laboratory of Geo-Information Science and Remote Sensing, Wageningen, Niederlande, .

    • Risse, Benjamin (): ‘Interdisciplinary Research at the Interface of Biology and Computer Vision / Pattern Recognition’. Institute for Evolution and Biodiversity, Münster, Germany, .
    • Risse, Benjamin (): ‘Visual Tracking of Small Animals in Cluttered Natural Environments Using a Freely Moving Camera’. International Conference on Computer Visioin (ICCV), Venice, Italy, .
    • Risse, Benjamin (): ‘Imaging and Tracking in Neurobiology: Acquiring Locomotion Trajectories of Small and Translucent Animals’. Cells in Motion: New Horizons in Experimental Medicine, Münster, Germany, .

    • Risse, Benjamin (): ‘Multimodal and adaptive behaviour in insects and robots’. School of Computer Science, Lincoln, UK, .
    • Risse, Benjamin (): ‘Imaging and Tracking of Semi-Translucent Animals like Worms or Larvae Using the FIM Multi-Purpose Setup ’. Centre of Integrative Physiology, Edinburgh, UK, .
    • Risse, Benjamin (): ‘Is Science Mostly Driven by Tools or by Ideas?’ Center for Integrative Biology, Toulouse, France, .
    • Risse, Benjamin (): ‘Insect Robotics’. Living Machines Workshop Satellite Presentation, Edinburgh, UK, .

    • Risse, Benjamin (): ‘Imaging and Tracking in Neurobiology’. IPAB Workshop, Edinburgh, UK, .
    • Risse, Benjamin (): ‘Acquiring Locomotion Trajectories of Drosophila melanogaster’. European Neuroscience Institute (ENI), Göttingen, Germany, .
    • Risse, Benjamin (): ‘Tracking and Imaging in Neurobiology using FIM’. Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany, .
    • Risse, Benjamin (): ‘Imaging Modalities for Semi-Translucent Animals and Their Impact on Quantitative Analysis’. Visual Obervation and Analysis of Vertebrate and Insect Behavior Workshop, ICPR 2014, Stockholm, Sweden, .
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    • Risse, Benjamin (): ‘Acquiring Locomotion Trajectories of Drosophila melanogaster’. Southwestern University of Finance and Economics, Sichuan, China, .