Vision Algorithm

Vision algorithms aim to enable computers to "see" and interpret images, facilitating tasks ranging from object detection and tracking to autonomous navigation and medical image analysis. Current research emphasizes efficient algorithm execution on resource-constrained devices (like edge platforms and embedded systems), utilizing architectures such as convolutional neural networks, spiking neural networks, and vision transformers, often optimized for specific hardware (e.g., FPGAs, GPUs). These advancements are crucial for diverse applications, including improved safety and security systems, advanced robotics, and enhanced medical diagnostics, driving progress in both computer vision and related fields.