Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

This technique can be used out-of-the-box, requiring no model training or special packaging. It is code-execution free, which ...
IEEE

Optimized Ensemble Learning for Semantic Segmentation of Satellite Imagery Using DeepLabV3+ and UNet With PSO and Cross-Dataset Evaluation

Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
IEEE

Pioneering Video Semantic Segmentation with Light Field Imaging and Spatial-Angular Temporal Fusion

Abstract: Video semantic segmentation aims to assign a semantic label to each pixel in a video by jointly exploiting spatial context and temporal coherence, and it is essential for applications such ...
The Conversation

Your sense of self is deeply tied to your memory – here’s how

Edith Cowan University provides funding as a member of The Conversation AU. You might say you have a “bad memory” because you don’t remember what cake you had at your last birthday party or the plot ...
Forbes

Semantic Leakage Is Taking A Hefty Toll On AI Producing Harmonious Mental Health Advice

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the role that semantic leakage ...
Fast Company

Market segmentation, AI and everything in between

When it comes to market segmentation, I don’t see truly well-documented cases often. At a more simplistic level, we think of classic matrices such as BCG or McKinsey’s. But the real exercise of ...
GitHub

semantic-segmentation-models

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet ...
Forbes

If Age Drives Your Segmentation, Behavior Should Lead Your Strategy

Marketers have long relied on simple demographic categories, including age, gender, income and region, to build segments and classifications. It’s convenient, easily understood and readily available ...
Frontiers

Radiomics-based machine learning model for predicting clinically ineffective reperfusion in acute ischaemic stroke patients after endovascular treatment

Background: Patients with acute ischaemic stroke (AIS) undergoing endovascular treatment may have a poor prognosis, even with successful recanalization. This study aims to evaluate a machine learning ...