> Markdown version of [/playlists/computer-vision](https://www.wearedevelopers.com/playlists/computer-vision). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Playlist: Computer vision 16 videos · 19 moments · 44.6 minutes ## Computer Vision from the Edge to the Cloud done easy - **Practical applications and use cases for computer vision** (00:20, 5min) — Real-world scenarios demonstrate how cameras act as digital sensors for retail, public safety, and smart cities. - **Components and architecture of computer vision systems** (06:16, 2min) — The core technical pipeline involves capturing video, storing footage, processing logic via inference, and displaying results on a dashboard. [Learn more](https://www.wearedevelopers.com/videos/263-computer-vision-from-the-edge-to-the-cloud-done-easy) ## How I built my own intelligent Robot Arm from Scratch - **Overcoming software challenges and future computer vision project integrations** (21:00, 2min) — Planning integrations with local language models and computer vision helps bypass frustrating software dependencies in traditional operating systems. [Learn more](https://www.wearedevelopers.com/videos/100097-how-i-built-my-own-intelligent-robot-arm-from-scratch) ## Detect Hand Pose with Vision - **Introduction to the Apple Vision framework** (01:54, 2min) — The Vision framework provides native support for complex computer vision tasks like image classification and real-time activity detection. [Learn more](https://www.wearedevelopers.com/videos/135-detect-hand-pose-with-vision) ## Focoos AI: Building the Future of Computer Vision - **Overcoming inefficiencies in computer vision modeling** (00:05, 0min) — Challenges in running computationally complex models on low-power edge devices require moving beyond inefficient trial and error methods. - **Optimizing computer vision models for edge devices** (01:53, 0min) — Proprietary optimizations produce efficient computer vision models that increase inference speeds and reduce computational complexity while retaini... - **Streamlining computer vision development workflows and platform tooling** (00:56, 0min) — A comprehensive development platform and synchronized open-source library provide end-to-end tooling spanning dataset handling through model deploy... [Learn more](https://www.wearedevelopers.com/videos/1659-focoos-ai-building-the-future-of-computer-vision) ## How AI Models Get Smarter - **Overcoming human limitations in the pre-transformer computer vision era** (04:16, 1min) — Reliance on manually labeled data created significant bottlenecks for legacy architecture scaling. [Learn more](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) ## The shadows of reasoning – new design paradigms for a gen AI world - **From crafted algorithms to deep learning and pattern recognition** (00:04, 3min) — How computer vision evolved from human-designed filters to deep learning models that independently identify complex patterns. [Learn more](https://www.wearedevelopers.com/videos/1000-the-shadows-of-reasoning-new-design-paradigms-for-a-gen-ai-world) ## How computers learn to see – Applying AI to industry - **Advantages of AI over classical computer vision** (02:03, 2min) — Automated AI algorithms bypass complex feature engineering to reliably detect manufacturing anomalies. [Learn more](https://www.wearedevelopers.com/videos/756-how-computers-learn-to-see-applying-ai-to-industry) ## WeAreDevelopers LIVE - Can AI save Accessibility?; Horrid HTML; The Frontend Treadmill and more - **Relying on artificial intelligence for captions and environment mapping** (24:34, 4min) — How automated transcription and computer vision applications physically assist users with real-time interpretation. [Learn more](https://www.wearedevelopers.com/videos/1318-wearedevelopers-live-can-ai-save-accessibility-horrid-html-the-frontend-treadmill-and-more) ## What non-automotive Machine Learning projects can learn from automotive Machine Learning projects - **Improving computer vision resilience using augmentation and out-of-distribution sampling** (35:29, 2min) — Combining multiple synthetic image alterations to reduce sensory data drift issues. [Learn more](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) ## Using Containers to deploy AI Models across our microscopy platform - **Exploring common AI workflows in microscopy tasks** (01:21, 1min) — How computer vision handles classification and instance segmentation of biological samples. [Learn more](https://www.wearedevelopers.com/videos/1127-using-containers-to-deploy-ai-models-across-our-microscopy-platform) ## RPA in the Public Sector - **Progressing from standard robotics to cognitive learning systems** (14:10, 2min) — Combining basic software robots with natural language processing and computer vision creates powerful cognitive automation. [Learn more](https://www.wearedevelopers.com/videos/86-rpa-in-the-public-sector) ## Mastering Image Classification: A Journey with Cakes - **Testing human visual accuracy against multiple machine learning models** (21:35, 3min) — An interactive demonstration comparing human visual detection against various evaluated computer vision programs to measure accuracy. [Learn more](https://www.wearedevelopers.com/videos/1272-mastering-image-classification-a-journey-with-cakes) ## Robots 2.0: When artificial intelligence meets steel - **Processing real-world environments with vision language models** (10:18, 0min) — Vision language models act as central intelligence hubs by fusing visual input with semantic understanding for autonomous decisions. [Learn more](https://www.wearedevelopers.com/videos/1452-robots-2-0-when-artificial-intelligence-meets-steel) ## Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML - **Manual data pre-processing using custom vision platforms** (15:54, 2min) — Training a custom vision model manually reveals the limitations and time constraints of non-automated data labeling. [Learn more](https://www.wearedevelopers.com/videos/78-leverage-cloud-computing-benefits-with-serverless-multi-cloud-ml) ## Industrializing your Data Science capabilities - **Centralizing telemetry aggregation pipelines and computer vision labeling** (37:43, 3min) — Combining automated imagery categorization and vehicle metrics feeds broader predictive maintenance alerting loops successfully. [Learn more](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities) ## Unleashing the Full Potential of the Arm Architecture – Write Once, Deploy Anywhere - **Optimizing computer vision pipelines with KleidiCV integration** (10:11, 0min) — How collaborative development within the OpenCV community achieves significant image processing performance uplifts. [Learn more](https://www.wearedevelopers.com/videos/940-unleashing-the-full-potential-of-the-arm-architecture-write-once-deploy-anywhere)