AI Just Got Better at Counting Trees
8 Oct 2025
Deep learning meets forestry: TreeLearn improves tree segmentation accuracy across diverse forest types using multi-domain training.
Accurate Forest Mapping Using TreeLearn and Lidar-Based Point Clouds
8 Oct 2025
TreeLearn uses deep learning on Lidar forest data to accurately segment, classify, and map individual trees in 3D environments.
AI Models Can Now Identify Individual Trees from Forest Scans
8 Oct 2025
AI models trained on diverse forest scans show promise for general tree segmentation, advancing 3D mapping and carbon analysis.
The Tortoise and the Hare: An Unexpected Scheduling Race Between MILP and CP Solvers
21 Sept 2025
This paper compares MILP and CP solvers on a new FJS scheduling problem, showing CP is faster and "warm starts" are vital for large instances.
Pitting Heuristics Against Exact Solvers in the Flexible Job Shop Gauntlet
21 Sept 2025
A performance showdown for Job Shop scheduling. This study pits MILP, CP, and new heuristics against a fresh set of challenging problem instances.
Algorithms That Learn as They Schedule: A Twin-Model Approach to Modern FJS
12 Sept 2025
This article formalizes DAG-based FJS with position-based learning via a MILP using position variables plus a CP Optimizer model.
Faster as You Go: Cracking Job-Shop Puzzles Where Tasks Learn on the Line
12 Sept 2025
Constructive heuristics jump-start MILP/CP on 12-machine tests, laying ground for future metaheuristics in modern FJS variants.
Add New Items, Not New Weights - Personalize Detection Without Backprop
10 Sept 2025
Object-conditioned prototypes plus stats beat FT even with 1-shot, 1-sequence data, and add only 0.8% latency to YOLOv8-n inference.
Few-Shot Personalization of YOLOv8 with Object-Conditioned Bags of Instances
10 Sept 2025
Multi-order stats enrich embeddings, avert neural collapse, and boost cross-domain accuracy while supporting lifelong instance updates.