Artificial Intelligence

<div style="color: #d4d4d4; background-color: #1e1e1e; font-family: Consolas, 'Courier New', monospace; font-size: 18px; line-height: 24px; white-space: pre;">Weakly-supervised segmentation (WSS) has emerged as a solution to mitigate the conflict between annotation cost and model performance by adopting sparse annotation formats (e.g., point, scribble, block, etc.). Typical approaches attempt to exploit anatomy and topology priors to directly expand sparse annotations into pseudo-labels.
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Wi-Fi FTM RSSI Localization dataset
Wi-Fi Fine Time Measurement for positioning / Indoor Localization in 3 different locations and using 8 different APs
Custom APs using ESP32C3 and Raw FTM is measured in nanoseconds
Data is only measured at the Router Side
Data is not measured at client side
Has 4 datasets inside the zip folder with over 100,000 data points
Contains processed Wi-Fi FTM packets from various routers in:
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Wi-Fi BLE RSSI SQI Localization dataset
Wi-Fi BLE RSSI for positioning / Indoor Localization in 4 different locations and using 18 different APs
Data is only measured at the Router Side
Data is not measured at client side
Has 12 datasets inside the zip folder with over 1,000,000 data points
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This is the supplementary document for the review paper titled “Comprehensive and Data-Driven Literature Review of Supernumerary Robotic Limbs,” which presents a comprehensive and data-driven review that offers a quantitative analysis of Supernumerary Robotic Limbs (SRLs), covering application areas, structural designs, control strategies, embodiments, and their interconnections.
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This is the official Thaat and Raga Forest (TRF) Dataset
Please do cite our paper: Link to Paper
Dataset is also available here: Link to Dataset
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This corpus comprises a diverse collection of authentic dialogues extracted from clinical encounters and from AI-generated interactions. Encompassing a wide array of scenarios, it offers a comprehensive snapshot of human communication within medical contexts and the evolving capabilities of AI. By intertwining genuine exchanges with those produced by AI models, the corpus facilitates a deeper understanding of communication dynamics and the progression of AI technology in simulating human interactions.
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Autistic people typically need methodical support as they explore and interact with their immediate surroundings and the objects associated with them, emphasising the importance of spatial knowledge and cognitive skills in improving and understanding their surroundings. The objective of this research paper is to present a conceptual and technical framework that could be of significant assistance in developing spatial ability and cognitive skills in autistic people.
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The emergence of SARS-CoV-2 lineages derived from Omicron, including BA.2.86 (nicknamed “Pirola”) and its relative, JN.1, has raised concerns about their potential impact on public and personal health due to numerous novel mutations. Despite this, predicting their implications based solely on mutation counts proves challenging. Empirical evidence of JN.1’s increased immune evasion capacity in relation to previous variants is mixed.
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This dataset contains RF (Radio Frequency) signals obtained from simulations, which model ultrasound propagation in cortical bone.
The simulations were designed to provide insights into the behaviour of ultrasound waves in cortical bone tissues, both in intact and pathological conditions. The dataset covers a wide range of parameters, including varying thickness (1-8 mm), porosity (1-20%), and frequency (1-8 MHz), allowing to explore the impact of these factors on ultrasound signal characteristics.
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The Partial Discharge - Localisation Dataset, abbreviated: PD-Loc Dataset is an extensive collection of acoustic data specifically curated for the advancement of Partial Discharge (PD) localisation techniques within electrical machinery. Developed using a precision-engineered 32-sensor acoustic array, this dataset encompasses a wide array of signals, including chirps, white Gaussian noise, and PD signals.
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