Convolutional Neural Networks: Analysis and Practice
Overview of convolutional neural networks: how filters, sliding-window local matching, convolution, ReLU activations, and pooling produce feature maps for image classification.
Overview of convolutional neural networks: how filters, sliding-window local matching, convolution, ReLU activations, and pooling produce feature maps for image classification.
Technical overview of voice recognition (ASR) in communications: development, mobile and smart home applications, assistive uses, and future trends with 5G.
Technical overview of compute scheduling in the compute network, covering orchestration, cross-domain scheduling, cost and latency tradeoffs, and platform architecture.
Technical overview of AI agents: how they use machine learning and multimodal data to perform tasks, make decisions, and enable applications in healthcare and autonomy.
RZ/A2M MPU for high-speed embedded AI image processing: hybrid DRP preprocessing tightly coupled with a Cortex-A9 CPU, up to 4MB SRAM and multiple PWM outputs.
MAX78002 evaluation kit overview: modular I/O for AI prototyping, supporting DVP/CSI cameras, I2S audio/mics, QWIIC expansion, power measurement and debug headers.
Step-by-step deployment guide for Janus-Pro on Orange Pi AI Pro (20T) using MindSpore v2.5.0 and MindSporeNLP, covering environment setup, swap, and examples.
Human keypoint detection guide covering API, model deployment, example code, 17-point keypoint mapping and benchmark runtime (53–93 ms) on EASY-EAI Orin-Nano.
Technical overview of differential scanning calorimeter capabilities and selection: measuring polymers, metals, chemical kinetics, pharma and food stability, and DZ-DSC models.
Hands-on review of the ELF 2 learning board with RK3588: hardware, documentation, embedded Linux and AI tutorials, multimedia interfaces, expandability and suggested improvements.
Edge AI and vision sensors overview: embedded ML platforms, real-time image processing, depth sensing, and on-device inference for industrial, smart city, and IoT applications.
Technical overview of microprocessors in AI: core roles, application cases (edge, autonomous vehicles, smart manufacturing), key challenges (power, data, security) and trends.
Overview of machine learning paradigms, deep learning fundamentals, and Edge AI deployment—advantages, use cases, and implications for low-latency, on-device processing.
Overview of Analog Devices' MAX78002 MCU with integrated CNN accelerator for edge AI: architecture, low-power SIMO/DVS power management, interfaces, and EV kit.
Technical overview of the iW-RainboW-G58M SoM with Intel Agilex 5 FPGA for edge AI, covering AI tensor acceleration, software toolchain and lifecycle support.
RK3576-based AI gateway for power station buildings: hardware selection, interfaces (UART, Ethernet, video), Linux performance and multi-sensor fault monitoring.