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[…] videos taken in carefully controlled environments like physiology laboratories or the Olympic games. Uncontrolled datasets aggregate user -captured videos often taken in unstructured, highly variable, environments like homes, neighborhood fields, and garages. Computer vision algorit hms for action recognition perform consistently well on controlled datasets, with high accuracy scores (>90%). But, action recognition accuracy […]

[…] cognitively impaired older adults ● Dr . Clara Berridge, Assistant Professor , School of Social Work, University of W ashington: older adults and their children, on in- home surveillance and monitoring systems ● Dr . Jon Antin, Human Factors Research Scientist, VA T ech: outreach initiatives for coordinating public/private services for the aged ● […]

[…] zones or corridor analysis). Some factors [5] to consider include:  Direct identifiers can be used to identify a particular person without additional information (e.g., rider names, home address, or transaction information).  Indirect (or quasi -) identifiers do not identify a specific individual alone, but can be aggregated and ” linked ” with […]

[…] owner, driver, passengers, and people outside of the vehicle. Similarly, “automobile data processors” is also defined fairly broadly and includes vehicle manufacturers, hardware and software suppliers, dealers, repair shops, and ride-hail companies.  Also notable are the references to and emphasis on driving safety. As vehicles become more connected and automated, safety standards will increasingly […]

[…] social center or safe space for “gay clubs.” The mayor of Seoul stated that those “exposed who do not come forward for testing will be visited at home accompanied by police,” which some fear puts LGBT popu – lations at risk of discrimination and speculation about individuals’ sexuality as a result of such tracing […]

[…] preparation, following the appropriate steps for that individual’s finances. Natural language processing (NLP) systems are some of the most common AI systems that people routinely encounter. Powering home-based assistants, and various devices or appliances; providing language translation tools, predictive typing, autocorrect, question and answer systems, and robotic speech; summarizing and analyzing written texts, and […]

[…] preparation, following the appropriate steps for that individual’s finances. Natural language processing (NLP) systems are some of the most common AI systems that people routinely encounter. Powering home-based assistants, and various devices or appliances; providing language translation tools, predictive typing, autocorrect, question and answer systems, and robotic speech; summarizing and analyzing written texts, and […]

[…] DPAs to introduce consolidated and consistent enforcement across Europe. тЦа (3) Prioritizing the protection of children and other vulnerable groups (e.g. elderly, non -native speakers and the home less). This includes publishing specific and accessible guidance, notably 22 on data sharing with third parties and consent. Other proposed initiatives include: тЦа Actively promoting the […]

[…] DPAs to introduce consolidated and consistent enforcement across Europe. тЦа (3) Prioritizing the protection of children and other vulnerable groups (e.g. elderly, non -native speakers and the home less). This includes publishing specific and accessible guidance, notably 22 on data sharing with third parties and consent. Other proposed initiatives include: тЦа Actively promoting the […]

[…] the digital economy more broadly.   It also looks like this consolidated regulatory regime is becoming a tool for Chinese regulators to assert their economic interests both at home and abroad and to effectuate broader policy goals in the geopolitical arena. For example, Didi’s cybersecurity review may be more directly related to other regulatory goals, […]