“Alissa Hattman’s Sift is gorgeous, fierce, and wise. In this dystopian, woman-centric landscape, the boundaries between internal and external reality are shimmeringly porous, and heartbreak …

Here you will find invitations to engage with Alissa Hattman’s Sift from different and intersecting vantages. The contributors are writers, artists, teachers, scholars, community leaders, and …

Alissa Hattman’s Sift is an extraordinarily palpable rendition of how love and grief might be reshaped by our still-unfolding climate crisis.

This means more work for us as we have to sift through low quality submissions. Because of this, before putting ergot. on a list or newsletter, we ask that you first contact us to ask permission …

May 4, 2023 · From tech company employees who’d like to sift through users’ messages, looking for someone they can turn in for a bounty. To show that Democratic lawmakers really care …

As the context size increases with the built-in recurrence, the system identifies and corrects its own errors. Our approach yields state-of-the-art performance on both the Stanford …

Various descriptors such as SIFT (Lowe, 2004) and HOG (Dalal & Triggs, 2005) offer a more robust representation, and have been highly successful in many computer vision applications.

As the context size increases with the built-in recurrence, the system identifies and cor-rects its own errors. Our approach yields state-of-the-art performance on both the Stanford Back …

Based on this, we propose a gradient-based sparse fine-tuning algorithm, named $\textbf {S}$parse $\textbf {I}$ncrement $\textbf {F}$ine-$\textbf {T}$uning (SIFT), and validate its …

Thus a crit-ical challenge for automatic scene recognition lies in the semantic gap between the low-level image features, such as the local gradient-based SIFT and HOG features (Lowe, …