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Earlier sources: Fusion
This energy thread follows fusion through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
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Open in the map ↗127 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Dual-stream attention and feature fusion for human activity recognition via wearable sensors ↗
Abstract Multi-sensor-based human activity recognition (HAR) has attracted considerable attention in recent years. Despite significant advancements achieved through deep learning, extracting refined and subtle features from multiple sensors placed on different parts of the body remains a challenge. Accurate sensor modality attention and temporal information processing are crucial for enhancing model performance. In this paper, we propose a new Temporal and Sensor-Modality Attention with Feature Fusion Network (TSFF). TSFF consists of two modules: the Temporal and Sensor Modality Attention bloc…
- OpenAlex · Published · First archived
Development of New Al-Ca-Cu-Mn-Zr Alloys for Laser Powder Bed Fusion ↗
The limited thermal stability of conventional aluminium alloys at elevated temperatures restricts their application in laser powder bed fusion (LPBF). In this study, a novel Al6Ca3Cu1.8Mn0.4Zr (wt.%) alloy was developed for improved thermal stability via stable intermetallic phases. LPBF processing of gas-atomised powder identified a reference processing window at 350 W and a hatch distance of 0.08 mm (~97–122 J·mm−3), enabling fabrication of crack-free samples with relative densities above 99.0%. The as-built microstructure consists of a highly refined cellular structure with a quasi-continuo…
- OpenAlex · Published · First archived
A Lightweight Multi-Sensor Feature-Level Fusion Framework for Noise-Robust Fault Diagnosis of High-Precision Milling Machines ↗
The operational reliability of milling machines is a critical factor affecting manufacturing quality and productivity in modern industrial systems. Although multi-sensor fusion can overcome the limitations of single-sensor monitoring, many existing methods rely on computationally intensive deep learning models, which restrict their applicability in resource-constrained industrial environments. To address this issue, this paper presents a multi-sensor feature-level fusion framework for fault diagnosis in high-precision milling machines. The proposed framework integrates vibration signals from t…
- OpenAlex · Published · First archived
ReViT-RF: A hybrid ResNet-50–Vision Transformer with a Radiomic Feature Fusion framework for lung tumor classification and TNM-based stage prediction using CT images ↗
Lung cancer is one of the leading causes of cancer-related mortality worldwide, emphasizing the need for accurate, automated, and clinically interpretable diagnostic systems. Although existing deep learning (DL) models have achieved promising performance in classifying lung nodules as benign or malignant, most approaches are limited to binary classification and provide insufficient support for detailed tumor characterization and TNM staging. Furthermore, conventional convolutional neural networks (CNNs) are effective in extracting local morphological features but often fail to capture long-ran…
- OpenAlex · Published · First archived
Graph-Enhanced Structural Reasoning for Feature-Fusion-Based Character Line-Art Segmentation ↗
Conventional pixel-wise segmentation does not fully exploit long-range relations among semantic components in character line drawings, where sparse textures, broken strokes, and overlapping contours make local evidence unreliable. We propose a graph-enhanced structural reasoning framework built on adaptive multi-level feature fusion. Hierarchical visual features are aligned and spatially reweighted to preserve fine strokes, part-scale structure, and global semantics. Soft component assignments induce a structural graph whose nodes represent semantic prototypes and whose edges combine learned f…
- OpenAlex · Published · First archived
VBT-Fusion: Branch-Selective Language Conditioning for Infrared–Visible Image Fusion ↗
Infrared–visible image fusion must reconcile different sensor roles: infrared imagery provides illumination-robust thermal evidence, whereas visible imagery supplies richer but illumination-sensitive structures and textures. Existing vision–language fusion methods show that textual context can guide reconstruction, but they rarely examine where language should enter a modality-specific network. We propose VBT-Fusion, a branch-selective language-conditioning framework for infrared–visible fusion. A precomputed language sequence interacts only with the visible branch, while the infrared represen…
- OpenAlex · Published · First archived
Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks ↗
Traditional human activity recognition systems in wearable technologies typically separate sensing modalities, using mechanical sensors for motion detection and biophysical sensors such as electrocardiography for health monitoring. This work challenges that division by demonstrating that electrocardiographic signals captured via textile electrodes inherently encode activity‐specific information, as motion‐induced signal deformations, traditionally dismissed as noise, carry discriminative patterns. A smart textile system was developed integrating textile‐based electrocardiographic electrodes an…
- OpenAlex · Published · First archived
From Linear Regression to Temporal Fusion Transformers: Benchmarking Electricity Price Forecasting Models in Markets with Different Renewable Energy Shares ↗
Rising renewable penetration increases wholesale price volatility and challenges traditional forecasting approaches. This paper benchmarks three methods—adaptive linear regression, Random Forest (RF), and the Temporal Fusion Transformer (TFT)—on hourly day-ahead prices in four European markets with contrasting generation mixes: Slovakia (nuclear-dominated), Spain (solar-rich), Denmark (wind-dominated), and Germany (mixed). Using Energy-Charts data for 2015–2025, all the models are evaluated under one day-ahead protocol on a common 12-month hold-out against naive 24-h persistence. With price-hi…
- OpenAlex · Published · First archived
APFNet: An Adaptive Perception Fusion Network for Multi-Scale Object Detection in Remote Sensing ↗
Accurate multi-scale object detection remains challenging in remote sensing (RS) imagery due to severe scale variation, limited pixel occupancy of small targets, and complex backgrounds. Existing multi-scale fusion methods propagate features along predefined cross-scale paths and apply receptive fields fixed once trained, so fusion weights and the spatial range of contextual evidence remain largely input-independent. The Adaptive Perception Fusion Network (APFNet) targets these two aspects through four operations: (1) Split-ELAN (SP-ELAN), a channel-compressed serial refinement backbone whose…
- OpenAlex · Published · First archived
DPFusion: Detail-preserving dual-path infrared and visible image fusion in high-radiance thermal scenes ↗
Infrared and visible image fusion integrates thermal radiation responses with visible textures, providing complementary information for observing high-radiance thermal targets. Most existing deep fusion methods enhance single-modality features before cross-modal fusion; the enhancement supplements context but tends to weaken original edges and weak textures and causes modality bias under strong thermal responses. This paper therefore proposes DPFusion, a detail-preserving dual-path fusion network with a three-scale dual-stream encoder, a parallel residual fusion (PRF) module, and a shared deco…
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How to assess evidence about Fusion
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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