Artificial Intelligence
The B2F dataset (Biometric images of Fingerprints and Faces) has been prepared for face and fingerprint recognition, verification or classification.
The first subset (Fingerprint): This set of data presents the five finger feature vectors (of the left hand) for each person in a csv files.
The second subset (Face): This set of data presents feature vectors of face images in csv files. Feature vectors were extracted using the model (ResNet-50 + ArcFace). This set of face feature vectors represents:
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The Dravidian Spam SMS dataset has Spam and Ham messages in English, Tamil, Telugu, Kannada, and Malayalam languages. Nearly 7700 messages were collected by sending friends and other contacts a Google form. Language experts (reading and writing skills) were used to label the messages of corresponding languages carefully. The dataset also includes the Tamil verbatim messages written in English. For example, “Nee Nalama”. The Ham messages are mostly normal. Spam messages include business, annoying, and unnecessary messages an anonymous user sends.
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The Customer log dataset is a 12.5 GB JSON file and it contains 18 columns and 26,259,199 records. There are 12 string columns and 6 numeric columns, which may also contain null or NaN values. The columns include userId, artist, auth, firstName, gender, itemInSession, lastName, length, level, location, method, page, registration, sessionId, song,status, ts and userAgent.
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A novel image deblurring dataset for materials science and light-optical microscopy. This dataset provides images with real out-of-focus and motion blur and a sharp reference image for each observation. The dataset includes image samples of lithium-ion batteries, Fe-Nd-B sintered magnets, 100Cr6 steel with a partially bainitic microstructure, and aluminium-silicon casting alloys. The dataset was acquired using a ZEISS AxioImager.Z2 Vario light microscope and the 6-megapixel camera Axiocam 506 color.
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Visual storytelling refers to the manner of describing a set of images rather than a single image, also known as multi-image captioning. Visual Storytelling Task (VST) takes a set of images as input and aims to generate a coherent story relevant to the input images. In this dataset, we bridge the gap and present a new dataset for expressive and coherent story creation. We present the Sequential Storytelling Image Dataset (SSID), consisting of open-source video frames accompanied by story-like annotations.
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Seed quality has become increasingly important in seed management and operation. Seed germination testing is one of the crucial methods for seed quality assessment, as the development quality of seeds, including germination rate and growth speed of seedlings, is an important indicator of seed quality. The germination rate of soybeans is one of the criteria for identifying high-quality soybeans.
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This dataset provides valuable insights into hand gestures and their associated measurements. Hand gestures play a significant role in human communication, and understanding their patterns and characteristics can be enabled various applications, such as gesture recognition systems, sign language interpretation, and human-computer interaction. This dataset was carefully collected by a specialist who captured snapshots of individuals making different hand gestures and measured specific distances between the fingers and the palm.
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The FMK (Finger Major Knuckle) dataset was proposed and created to support the experiments of identity verificatio of knuckles of middle and thumb fingers modalites. The images of this dataset were captured using the rear camera of an OPPO A12 smartphone. This dataset was created from 20 different subjects between the ages of 30 and 67. For each subject there are 3 images of major knuckle for the middle finger and 3 images of major knuckle for thumb finger.. The FMK dataset was proposed and constructed for testing and evaluation.
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We collated small molecule solubility data from an array of databases and literature. Some of these sources merely provided molecular names, lacking SMILES notation. We sourced the molecular SMILES and molecular weights from PubChem, DrugBank, https://www.wikiarabic.org/, and https://www.sigmaaldrich.com/US/en. In terms of data selection, Canonical SMILES was preferred over Isomeric SMILES in instances where both were available in different forms.
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Abstract—This paper presents a novel approach to optimizing resource allocation in Internet of Things (IoT) networks, focusing on enhancing energy efficiency (EE) while maintaining age of information (AoI) awareness through device-to-device (D2D) communication. Our proposed solution integrates simultaneous wireless information and power transfer (SWIPT) with energy harvesting (EH) techniques. Specifically, D2D users employ time switching (TS) to harvest energy from the environment, while IoT users utilize power splitting (PS) to obtain energy from base stations (BS).
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