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Building AI algorithms necessitates a proficient team and valuable data, both of which are crucial for effective training. Our team specializes in assisting with algorithm training, offering crowd support for search engine optimization, data collection, annotation, and validation. We are well-equipped to provide the necessary expertise and resources for successful AI development.
At Ants, we excel in curating pertinent datasets tailored to your model requirements. Our expertise lies in proficiently gathering data in diverse formats, encompassing images, videos, text, audio, and any other specific data that aligns with your unique needs. With our extensive experience, we ensure the collection of high-quality, relevant data to fuel the success of your AI models.
Our team possesses exceptional skills in delivering precise and dependable annotations for a wide range of datasets, encompassing images, videos, audio, and other specific data types. We specialize in an array of annotation tasks, including classification, segmentation, object detection, and much more. With our expertise, we guarantee accurate annotations that are crucial for training AI models .
We provide a comprehensive dataset validation service that ensures the quality and accuracy of previously collected and annotated data. With our vast experience in working with diverse clients and tasks, we possess the expertise to perform meticulous and thorough validation processes. Our validation services guarantee the reliability and integrity of your datasets, giving you confidence in the performance.
We take pride in our team's ability to consistently deliver exceptional results in the areas of page content ranking and semantic web clustering. Our extensive knowledge and expertise in these domains enable us to provide valuable insights and solutions that drive sustainable growth for your business. Whether you need assistance in optimizing your website's content for better ranking or organizing and categorizing web data.
Video Data Collection for Driver Safety Technology Development A hardware and software production company faced the challenge of developing a technology that could alert drivers about dangerous cell-phone usage and fatigue. To achieve this, they required a dataset of 150 hours of video featuring 50+ different people. Our solution involved organizing global data collection in Asian, Latin, and European countries. We provided special cameras to 80 drivers, who then recorded their journeys. Our dedicated collection team worked diligently to gather 500 hours of video footage. To ensure the quality and relevance of the collected data, our Quality Assurance team reviewed the videos. They carefully selected the most suitable footage that aligned with the client's requirements. Throughout the project, our dedicated project manager played a crucial role in overseeing the collection and validation processes. Their effective control and coordination ensured that collection deadlines were met, and the dataset provided was suitable for the technology's creation. As a result of our high-quality video data collection service, the client was able to successfully develop their driver safety technology. The dataset we provided served as a valuable resource in the creation and testing of their innovative solution, enabling them to address the challenges of dangerous cell-phone usage and fatigue among drivers.
Objective: The client wanted to improve the efficiency of fertilizers used in agriculture by developing a technology that could predict the optimal time and location to apply chemical fertilizers, and distribute them evenly across the field. Solution: Our team was commissioned to collect ground samples from different parts of the field and map agricultural fields using drones. Our technology involved developing an algorithm that could predict and advise the farmer on the optimal time and location to apply chemical fertilizers, and distribute them evenly across the field. Our contribution involved collecting ground samples from various parts of the field over a period of three years and sharing them with a lab. We also leveraged our network of partners to map the fields using drones, delivering the project on time. Outcome: Our technology allowed the client to optimize the application of chemical fertilizers, resulting in significant cost savings and improved crop yields. The client was able to reduce their fertilizer usage by 20%, resulting in a significant reduction in the environmental impact of their agricultural practices.
Objective: The client requested a dataset of 2000 dental CT scans and 2000 x-ray scans that cover 95%+ of the most common dental diseases. The aim was to develop an algorithm that can assist dentists in diagnosing and treating patients accurately. Solution: Our team, in collaboration with our healthcare partners, collected and annotated the required scans to ensure completeness, accuracy, and consistency of the dataset. We also contracted a dentist to support us during the entire collection and annotation process. By using our expertise in data collection and annotation, we were able to meet the client's deadline and provide a high-quality dataset for the development of the dental diagnostics algorithm. Outcome: The algorithm will assist dentists in making accurate diagnoses and treatment plans for their patients.
Objective: The client requested a unique dataset of over 10,000 images of human faces for face recognition in gym technology. The dataset needed to be collected and delivered within tight deadlines. Solution: Our global team and unique Quality Assurance processes were mobilized to collect and curate the required dataset. We ensured that the dataset was diverse and representative, covering a wide range of facial characteristics and variations. Our team completed the collection and Quality Assurance process within 2 weeks, well before the deadline. Outcome: The client was highly satisfied with the quality of the dataset. They were able to use it effectively to develop their face recognition technology for gyms. The dataset enabled them to train their algorithms accurately and efficiently, leading to improved recognition performance in their gym technology.
LabelingSegmentationBounding BoxesKey points
Cuboid3D scene built by LIDAR/RADAR or cameraCloud Points
SegmentationObject TrackingKey points Labelling
Key words TranscriptionAudio levelLabelling.
Sentiment AnalysisTranscriptionOptical character recognition
Objective: The company required accurate annotation of their image data with a minimum requirement of 95% accuracy and no more than 1% of objects missed. They decided to outsource this task to a crowd training team. Solution: The crowd training team was engaged to perform the annotation task. They were able to complete the training within one week, achieving an impressive accuracy rate of 98%. The team followed a meticulous process to ensure accurate and comprehensive annotation of the image data. Outcome: The client was delighted to discover that the project was finished two weeks ahead of schedule, allowing them to proceed with their subsequent tasks promptly. Additionally, the project cost was lower than expected, providing the company with cost savings. The high accuracy rate of 98% reassured the client that their image data was accurately annotated, meeting their requirements. The client was satisfied with the outcome and could confidently utilize the annotated data for their intended purposes.
2D Bounding box annotation for object detectionfor Video recorder technology
he client approached us with a large dataset of road images and tight deadlines for annotation. They required a high level of accuracy of 98%+ for bounding boxes and no more than 0.5% of objects missed. Solution: We assisted the client by providing guidance on dataset quality and filtered out repeated or similar images, resulting in a 20% decrease in annotation budget. Next, we divided the annotation process into three stages: first iteration, second correction, and verification. We trained 250 people for this project. Outcome: The project was completed on time with an accuracy rate of 98.4%+ for bounding boxes and only 0.4% of objects missed, exceeding the client's requirements. Furthermore, the client spent 20% less than originally budgeted. The client was satisfied with our work and provided us with additional projects. This use case demonstrates our ability to provide high-quality annotation services while also helping clients optimize their budgets and achieve their desired outcomes.
Objective: A client approached us with a request for polygon annotation services with a requirement for an accuracy rate of 92%+ and no missed objects on the frame. Solution: 1. Dataset Revision: We started by revising the entire dataset with the help of our data validation team, filtering out duplicates and ensuring a high-quality dataset for annotation. 2. Annotation Process: We proceeded with the annotation process using a team of experienced annotators with over 6 months of experience. Outcome: 1. On-time Completion: The project was completed on time, meeting the client's deadline. 2. Cost Optimization: We were able to deliver the project within a budget that was lower than initially planned by the client. 3. High-Quality Results: The annotation services provided achieved an accuracy rate of 92%+ and ensured no missed objects on the frame. This use case demonstrates our ability to deliver high-quality annotation services with accurate results while also optimizing budgets for our clients.
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