"If nothing changes, all remaining Nitter instances will go down eventually"
Points: 503 | Comments: 359 | Author: proctrap
Show HN: Lambda function to make a hosts file from your running EC2 instances
Points: 2 | Comments: 0 | Author: andrewstuart
Spot VMs | Google Cloud
Spot VMs are highly affordable compute instances suitable for batch jobs and fault-tolerant workloads.
Cloud GPUs (Graphics Processing Units) | Google Cloud
Increase the speed of your most complex compute-intensive jobs by provisioning Compute Engine instances with cutting-edge GPUs.
Court of first instance (disambiguation) - Wikipedia
instance (Belgium) Tribunal of first instance (France) Court of First Instance (Hong Kong) Courts of First Instance of Peru General Court (European Union)
Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Ta…
Copy-Paste has proven to be a very effective data augmentation for instance segmentation which can improve the generalization of the model. We used a task-specific Copy-Paste data augmentation method to achieve good performance on the instance segmen...
Instance variable - Wikipedia
separate copy, or instance. An instance variable has similarities with a class variable, but is non-static. In C++ or Java language, an instance variable is
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Sema…
Weakly-supervised instance segmentation (WSIS) has been considered as a more challenging task than weakly-supervised semantic segmentation (WSSS). Compared to WSSS, WSIS requires instance-wise localization, which is difficult to extract from image-le...
Address Instance-level Label Prediction in Multiple Instance Learning
\textit{Multiple Instance Learning} (MIL) is concerned with learning from bags of instances, where only bag labels are given and instance labels are unknown. Existent approaches in this field were mainly designed for the bag-level label prediction (p...
ClickSeg: 3D Instance Segmentation with Click-Level Weak Annotations
3D instance segmentation methods often require fully-annotated dense labels for training, which are costly to obtain. In this paper, we present ClickSeg, a novel click-level weakly supervised 3D instance segmentation method that requires one point pe...
johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation
Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017). (⭐ 55)
Instance-based learning - Wikipedia
new problem instances with instances seen in training, which have been stored in memory. Because computation is postponed until a new instance is observed
terraform-aws-modules/terraform-aws-ec2-instance
Terraform module to create AWS EC2 instance(s) resources ?? (⭐ 800)
Instances
Am I crazy or is it impossible to finish the bagua, 3 immortals & roulette instances without ads? Or am I doing something wrong? It’s usually like a minimum of 6 ads or tickets to actually succe...
Hardness of SetCover Reoptimization
We study hardness of reoptimization of the fundamental and hard to approximate SetCover problem. Reoptimization considers an instance together with a solution and a modified instance where the goal is to approximate the modified instance while utiliz...
Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network
We present an instance segmentation algorithm trained and applied to a CCTV recording of beef cattle during a winter finishing period. A fully convolutional network was transformed into an instance segmentation network that learns to label each insta...
Latest Object Memory Management for Temporally Consistent Video Instance Segmentation
In this paper, we present Latest Object Memory Management (LOMM) for temporally consistent video instance segmentation that significantly improves long-term instance tracking. At the core of our method is Latest Object Memory (LOM), which robustly tr...
CAVIS: Context-Aware Video Instance Segmentation
In this paper, we introduce the Context-Aware Video Instance Segmentation (CAVIS), a novel framework designed to enhance instance association by integrating contextual information adjacent to each object. To efficiently extract and leverage this info...
TRACE: Your Diffusion Model is Secretly an Instance Edge Detector
High-quality instance and panoptic segmentation has traditionally relied on dense instance-level annotations such as masks, boxes, or points, which are costly, inconsistent, and difficult to scale. Unsupervised and weakly-supervised approaches reduce...
Mask-Attention-Free Transformer for 3D Instance Segmentation
Recently, transformer-based methods have dominated 3D instance segmentation, where mask attention is commonly involved. Specifically, object queries are guided by the initial instance masks in the first cross-attention, and then iteratively refine th...