This dataset is composed by both real and sythetic images of power transmission lines, which can be fed to deep neural networks training and applied to line's inspection task. The images are divided into three distinct classes, representing power lines with different geometric properties. The real world acquired images were labeled as "circuito_real" (real circuit), while the synthetic ones were identified as "circuito_simples" (simple circuit) or "circuito_duplo" (double circuit). There are 290 total images for each class, 232 inteded for training and 58 aimed for validation/testing.

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532 Views

There is an industry gap for publicly available electric utility infrastructure imagery.  The Electric Power Research Institute (EPRI) is filling this gap to support public and private sector AI innovation.  This dataset consists of ~30,000 images of overhead Distribution infrastructure.  These images have been anonymized, reviewed, and .exif image-data scrubbed.  These images are unlabeled and do not contain annotations.  EPRI intends to label these data to support its own research activities.  As these labels are created, EPRI will periodically update this dataset with those data.

Instructions: 

These images are not labeled or annotated.  However, as these images are labeled, EPRI will update this dataset periodically.  If you have annotations you'd like to contribute, please send them, with a description of your labeling approach, to ai@epri.com.

 

Also, if you see anything in the imagery that looks concerning, please send the image and image number ai@epri.com

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476 Views

To address the problem of online automatic inspection of drug liquid bottles in production line, an implantable visual inspection system is designed and the ensemble learning algorithm for detection is proposed based on multi-features fusion. A tunnel structure is designed for visual inspection system, which allows the bottles inspection to be automated without changing original processes and devices. A high precision method is proposed for vision detection of drug liquid bottles.

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170 Views

The dataset contains 236 X-ray images, all of which include the top of the head to the middle of the thigh. The included patients are 18-80 years old, and treated to the department of orthopedics due to low back pain or spinal deformity. The original size of the X-ray images is around 3000×7000px.

 

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830 Views

DIDA is a new image-based historical handwritten digit dataset and collected from the Swedish historical handwritten document images between the year 1800 and 1940. It is the largest historical handwritten digit dataset which is introduced to the Optical Character Recognition (OCR) community to help the researchers to test their optical handwritten character recognition methods. To generate DIDA, 250,000 single digits and 200,000 multi-digits are cropped from 75,000 different document images. 

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569 Views

Dataset including over 40,000 generated images of malicious binaries for malware classification in machine learning as outlined in NARAD - A Novel Auto-learn Real-time Fuzzy Machine Learning Anomaly Detection and Classification System.

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1330 Views

The dataset consists all the Telugu characters that contains Vowels, Consonants and combine characters such as Othulu (Consonant-Consonant) and Guninthamulu (Consonant-Volwels). The main objective of this dataset to recognize handwritten Telugu characters, from that convert handwritten document into editable electronic copy.

Instructions: 

All the images are in the same size and all images are scanned by scanner and segmented manually and all images are jpeg images.

 Acknowledgement:

 The work is carried out under Collaborative Research Project Sponsored by JNTU Hyderabad, India. The project file no. JNTUH/TEQIP-III/CRS/2019/CSE/12 and Titled as "Deep Learning Aided-OCR for Handwritten Telugu Character".

 

 

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1191 Views

The first bit of light is the gesture of being, on a massive screen of the black panorama. A small point of existence, a gesture of being. The universal appeal of gesture is far beyond the barriers of languages and planets. These are the microtransactions of symbols and patterns which have traces of the common ancestors of many civilizations.Gesture recognition is important to make communication between the computer system and humans, in the present era many studies are going on regarding the gesture recognition systems.

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102 Views

Mosquito bites result in the deaths of more than 1 million people every year.   Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.

Instructions: 

The dataset consists of images of two species of mosquitoes namely Aedes and Culex .  

There are 810 images of Aedes and 594 images of Culex class.

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1160 Views

Recognition and classification of currency is one of the important task. It is a very crucial task for visually impaired people. It helps them while doing day to day financial transactions with shopkeepers while traveling, exchanging money at banks, hospitals, etc. The main objectives to create this dataset were:

        1)      Create a dataset of old and new Indian currency.

        2)      Create a dataset of Thai Currency.

        3)      Dataset consists of high-quality images.

Instructions: 

The dataset consists of 10 classes namely 10 New, 10 Old, 20, 50 New, 50 Old, 100 New, 100 Old, 200, 500, 2000 of Indian banknotes and 5 classes namely 20, 50, 100, 500, and 2000 for Thai bank notes.

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1447 Views

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