What’s New in Computer Vision and Object Detection? | by TDS Editors | Jul, 2024 – Information Today Online

Feeling inspired to indite your prototypal TDS post? We’re ever unstoppered to contributions from newborn authors.

Before we intend into this week’s activity of stellar articles, we’d aforementioned to verify a time to impart every our readers, authors, and members of our broader accord for serving us fulfill a field milestone, as our mass calculate on Medium meet reached…

We couldn’t be more thrilled — and glad for everyone that has based us in making TDS the thriving, learning-focused playing it is. Here’s to more ontogeny and expedition in the future!

Back to our lawful business, we’ve chosen threesome past articles as our highlights this week, convergent on cutting-edge tools and approaches from the ever-exciting fields of machine exteroception and goal detection. As multimodal models acquire their print and ingest cases aforementioned free driving, healthcare, and cultivation go mainstream, it’s never been more pivotal for accumulation and ML practitioners to meet up-to-speed with the stylish developments. (If you’re more fascinated in another topics at the moment, we’ve got you covered! Scroll downbound for a containerful of carefully picked recommendations on neuroscience, penalization and AI, environmentally semiconscious ML workflows, and more.)

• Mastering Object Counting in Videos
  Accurate goal spotting in videos comes with a patron of newborn challenges when compared to the aforementioned impact in noise images. Lihi Voltaic Arie, PhD presents a country and apothegmatic tutorial that shows how you crapper ease fulfill it, and uses the recreation warning of reckoning agitated ants on a tree to attain her case.
• Spicing Up Ice Hockey with AI: Player Tracking with Computer Vision
  For anyone hunting for a complete and attractive send walkthrough, we strongly propose Raul Vizcarra Chirinos’ writeup of his past endeavor to physique a hockey-player tracker from (more or less) scratch. Using PyTorch, machine exteroception techniques, and a convolutional neuronal meshwork (CNN), Raul matured a image that crapper study players and amass base action statistics.
• A Crash Course of Planning for Perception Engineers in Autonomous Driving
  While we strength ease be eld absent from self-driving cars high our roads, researchers and business players hit prefabricated momentous advancement in past years. Practitioners who’d aforementioned to modify their noesis of thinking and decision-making in the environment of free dynamical shouldn’t woman Patrick Langechuan Liu’s broad “crash course” on the topic.