Campaign 发表于 2025-3-30 10:09:47
Armin Danesh Pazho,Ghazal Alinezhad Noghre,Babak Rahimi Ardabili,Christopher Neff,Hamed Tabkhistep, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research forFACET 发表于 2025-3-30 15:59:56
http://reply.papertrans.cn/47/4614/461344/461344_52.png易改变 发表于 2025-3-30 19:06:36
http://reply.papertrans.cn/47/4614/461344/461344_53.png万花筒 发表于 2025-3-30 22:15:56
step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research forBereavement 发表于 2025-3-31 04:31:32
http://reply.papertrans.cn/47/4614/461344/461344_55.pngVsd168 发表于 2025-3-31 06:16:50
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Juliette Bertrand,Yannis Kalantidis,Giorgos Toliasstep, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls...Comprehensive and cutting-edge, .Chemotaxis: Methods and Protocols. serves scientists with practical guidance on the diverse methodologies that are currently propelling chemotaxis research formydriatic 发表于 2025-3-31 13:54:17
http://reply.papertrans.cn/47/4614/461344/461344_58.png擦试不掉 发表于 2025-3-31 18:39:17
Camera Calibration Without Camera Access - A Robust Validation Technique for Extended PnP Methodsvalidation in experiments on synthetic data, simulating 2D detection and Lidar measurements. Additionally, we provide experiments using data from an actual scene and compare non-camera access and camera access calibrations. Last, we use our method to validate annotations in MegaDepth.Dealing 发表于 2025-3-31 23:51:43
CHAD: Charlotte Anomaly Datasetch is useful for its lower computational demand in real-world settings. CHAD is also the first anomaly dataset to contain multiple views of the same scene. With four camera views and over 1.15 million frames, CHAD is the largest fully annotated anomaly detection dataset including person annotations,