Computer vision
Latest stories covering Computer vision, with summaries and links to related coverage.
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SIMD-accelerated computer vision on a $2 microcontroller
research
5 min read
A SIMD-accelerated implementation of the FAST feature detector runs on Espressif’s ESP32-S3 microcontroller, using the chip’s 128-bit vector instructions to process 16 eight-bit pixels per vector register. The implementation processes a 320×240 QVGA frame in about 6 ms and increased measured throughput from 5.1 megapixels per second to 11.2 megapixels per second, a roughly 220% improvement over the reference implementation. The stated performance is sufficient to process a 30-frame-per-second VGA stream. The ESP32-S3 has a dual-core CPU clocked up to 240 MHz, Wi-Fi and Bluetooth Low Energy radios, and a limited SIMD instruction set. FAST identifies image features by comparing pixels around a center pixel; its pre-test samples pixels in the cardinal directions and looks for at least three whose intensity differs from the center by more than a threshold. The implementation handles the ISA’s lack of direct misaligned reads by extracting slices from adjacent vector registers. It also compensates for signed-only eight-bit SIMD comparisons and saturating arithmetic by XORing each unsigned pixel value with 0x80, mapping the 0–255 range into the signed −128–127 range without subtraction.
A 10-year-old CNN outperforms frontier LLMs for skin cancer diagnosis
opinion
5 min read
A dermatologist tested GPT-6 Astra, Claude Fable 5.1 and a fine-tuned Inception v3 convolutional neural network on 200 randomly selected, biopsy-confirmed skin lesions from the public MILK10k dataset. The CNN correctly identified 125 of 200 lesions across six diagnoses, or 62%, while GPT-6 Astra and Claude Fable 5.1 identified 84 and 85, or 42% each. Inception v3 was introduced by Google in 2015 and was fine-tuned on 68,011 ISIC Archive clinical and dermoscopic images for about 20 minutes on one H100 GPU. The test set contained 100 lesions requiring further care, including 30 melanomas, and 100 benign lesions considered safe to discharge. The CNN identified 13 melanomas as its first choice, versus eight for GPT-6 Astra and 11 for Claude Fable 5.1. With a second diagnostic choice allowed, the CNN reached 173 correct cases, compared with 134 and 138 for the LLMs. Both LLMs incorrectly labeled a pictured melanoma as a benign seborrhoeic keratosis and said the patient could be discharged. The sample size was small, each LLM response was generated once, and all lesions had been biopsied, making the cases unusually difficult. At its preset discharge threshold, the CNN discharged 18 melanomas, though matching its unsafe-lesion retention rate to the LLMs reduced that figure to two or one. The browser-based CNN runs locally with WebGPU and does not upload images.
Nikon photography contest winner loses title after scientists spot signs of AI
news
3 min read
Nikon stripped Dr. Ning Xu of the top prize in its 16th annual Small World in Motion contest after an investigation found that his microscopy video violated competition rules. Xu, a researcher at Tsinghua University in China, had submitted footage purportedly showing cilia beating in the airway of a child with primary ciliary dyskinesia, a rare respiratory disorder. Scientists questioned the clip after observing cellular structures with inconsistent sizes and forms that appeared and disappeared in ways they said do not occur in cellular biology. Ian Donovan, a PhD student at UT Southwestern Medical Center, said the apparent source image contained a watermark associated with AI-generated imagery, while two former contest judges also raised concerns. Xu later acknowledged using AI during post-processing to distinguish and visualize features in reconstructed grayscale super-resolution images, while denying that AI generated the video, cilia, or their movement. Nikon awarded the top spot instead to Nguyen Nam Nhat of Vietnam for a video featuring a tiny roundworm and a single-celled organism. Nikon said it will revisit its rules and evaluation procedures for future entries.